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Combining the demand for interim and opportunity charging - a case study from Stuttgart

Presented at EVS30, International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium & Exhibition, Stuttgart, Germany, 09-11 October, 2017
: Gnann, Till; Jochem, Patrick; Reuter-Oppermann, Melanie

Volltext urn:nbn:de:0011-n-4739955 (672 KByte PDF)
MD5 Fingerprint: d0801e3a2083ebb8371417d0cab1dc5b
Erstellt am: 24.11.2017

2017, 6 S.
International Electric Vehicle Symposium & Exhibition (EVS) <30, 2017, Stuttgart>
Vortrag, Elektronische Publikation
Fraunhofer ISI ()

The market share of plug-in electric vehicles (PEVs) has been increasing in the last years which comes along with a raising demand for public charging stations. While the operation of low-power charging stations (Mode-3) is far from being profitable, prospects for fast charging stations indicate attractive revenues. This is mainly based on a higher workload (shorter charging times), a higher willingness-to-pay of customers and a higher complementary situation compared to home-based charging [1]. Both also serve for different purposes: Slow charging is performed whenever there is an opportunity while fast charging will also allow short stops to recharge on long-distance trips (interim charging). In this paper, we investigate the potential for combining interim and opportunity charging at one location in order to increase the utilization and decrease the payback time of public fast charging stations. For modeling the operation of Mode-3 charging stations, we applied the ALADIN model [2] and combine it with results from an optimal allocation of fast charging points in Germany (cf. [3]). Results are presented for four fast charging stations around Stuttgart, Germany. Our results show that a combination of long-distance and local customers may increase the occupancy rate and therefore the profitability of fast charging stations. Yet, the willingness to detour of PEV users, the comparably small additional earnings for charging stations together with a joint optimized location modelling might be analyzed in further work.